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Multi-Asset Risk Modeling: Techniques for a Global Economy in an Electronic and Algorithmic Trading Era - Hardcover

 
9780124016903: Multi-Asset Risk Modeling: Techniques for a Global Economy in an Electronic and Algorithmic Trading Era

Inhaltsangabe

Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management.

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Über die Autorinnen und Autoren

Professor Morton Glantz serves as a financial consultant, educator, and adviser to a broad spectrum of professionals, including corporate financial executives, government ministers, privatization managers, investment and commercial bankers, public accounting firms, members of merger and acquisition teams, strategic planning executives, management consultants, attorneys, and representatives of foreign governments and international banks. Professor Morton Glantz is a principal of Real Consulting and Real Options Valuation, firms specializing in risk consulting, training, certification, and advanced analytical software in the areas of risk quantification, analysis, and management solutions.

As a JP Morgan Chase (heritage bank) senior banker, Professor Glantz built a progressive career path specializing in credit analysis and credit risk management, risk grading systems, valuation models, and professional training. He was instrumental in the reorganization and development of the credit analysis module of the Bank’s Management Training Program-Finance, which at the time was recognized as one of the foremost training programs in the banking industry.

Professor Glantz is on the (adjunct) finance faculty of the Fordham Graduate School of Business. He has appeared in the Harvard University International Directory of Business and Management Scholars and Research, and has earned Fordham University Deans Award for Faculty Excellence on three occasions. He is a Board Member of the International Standards Board, International Institute of Professional Education and Research (IIPER). The IIPER is a global institute with partners and offices around the world, including the United States, Switzerland, Hong Kong, Mexico, Portugal, Singapore, Nigeria, and Malaysia. Professor Glantz is widely published in financial journals and has authored 8 books.



Robert Kissell, Ph.D., is President of Kissell Research Group, a global financial and economic consulting firm specializing in quantitative modeling, statistical analysis, and algorithmic trading. He is also a professor at Molloy College in the School of Business and an adjunct professor at the Gabelli School of Business at Fordham University. He has held several senior leadership positions with prominent bulge bracket investment banks including UBS Securities where he was Executive Director of Execution Strategies and Portfolio Analysis, and at JP Morgan where he was Executive Director and Head of Quantitative Trading Strategies. He was previously at Citigroup/Smith Barney where he was Vice President of Quantitative Research, and at Instinet where he was Director of Trading Research. He began his career as an Economic Consultant at R.J. Rudden Associates specializing in energy, pricing, risk, and optimization. Dr. Kissell has written several books and published dozens of journal articles on Algorithmic Trading, Risk, and Finance. He is a coauthor of the CFA Level III reading titled “Trade Strategy and Execution,” CFA Institute 2019.”

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This single volume describes the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. With mathematics playing a prominent role, the authors present standard risk-management and asset allocation models and more advanced extensions, discuss the laws in standard models that contributed to the 2008 financial crisis, and talk about current and future banking regulation. Importantly, they also explore algorithmic trading, which currently receives sparse attention in the literature. Their focus on practical issues and their ability to translate difficult risk management material into practice with insights into the difficulties of implementation and techniques for the required parameter estimation set their volume apart from others. By giving coherent recommendations about which statistical models to use for which asset class, they make a real contribution to the sciences of portfolio management and risk management.|This single volume describes the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. With mathematics playing a prominent role, the authors present standard risk-management and asset allocation models and more advanced extensions, discuss the laws in standard models that contributed to the 2008 financial crisis, and talk about current and future banking regulation. Importantly, they also explore algorithmic trading, which currently receives sparse attention in the literature. Their focus on practical issues and their ability to translate difficult risk management material into practice with insights into the difficulties of implementation and techniques for the required parameter estimation set their volume apart from others. By giving coherent recommendations about which statistical models to use for which asset class, they make a real contribution to the sciences of portfolio management and risk management.

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  • VerlagAcademic Press
  • Erscheinungsdatum2014
  • ISBN 10 0124016901
  • ISBN 13 9780124016903
  • EinbandTapa dura
  • SpracheEnglisch
  • Anzahl der Seiten554
  • Kontakt zum HerstellerNicht verfügbar

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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management. Covers all asset classes Provides mathematical theoretical explanations of risk as well as practical examples with empirical data Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities 544 pp. Englisch. Bestandsnummer des Verkäufers 9780124016903

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Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management. Covers all asset classes Provides mathematical theoretical explanations of risk as well as practical examples with empirical data Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities. Bestandsnummer des Verkäufers 9780124016903

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